1. Field of the Disclosure
The present invention relates generally to image correction, and more specifically relates to automatic white balancing.
2. Background
The visual system of the human eye is capable of adapting to changes in lighting conditions. For example, when a person is viewing an object that is indoors, the illuminant source may be a light bulb, while when a person is viewing an object that is outdoors, the illuminant source may be the sun. When a white object travels from sunlight (which has more blue color component) to incandescent light (which has more red color component), the human visual system makes adjustment to balance the red, green, and blue color components to ensure that a white object appears white in both daylight and incandescent light. The technique of balancing the red color, green color, and blue color components is known as white balance. Thus, the human visual system automatically white balances an image to preserve the true white color of a white object in the image even as the white object reflects light from different illuminant sources. Image capture systems use automatic white balance (“AWB”) algorithms to attempt to mimic the human visual mechanism in order to reproduce the true white color of a white object in an image under different illuminant sources.
The strength of the RGB color components varies significantly in different light conditions. For example, there is far more blue color component in daylight, e.g., D65, than in interior cool white fluorescent (“CWF”) light. Table I provides a color temperature index for different illuminant types. Higher color temperature, such as daylight, e.g., D65, has more blue color component while lower color temperature, such as incandescent light, e.g., A, has more red color component.
TABLE IColor Temperature IndexIlluminant TypeColor TemperatureD65 (Daylight)6500KCWF (Cool White Fluorescent)4500KA (Incandescent Light)2000K
AWB methodology includes analyzing a captured image to determine its illuminant source and then, derives the amount of gain adjustment necessary to achieve white balance. The AWB mechanism examines the pixels of an image to obtain information on the illuminant source of the image. It also determines the gain adjustments needed for white balancing the image. The white pixels of an image contain information used to ascertain the white balance setting.
Prior art AWB methods presume that the whole image is under a single illuminant type and needs to be white balanced for the single illuminant type. However, the assumption of single illuminant type often results in a less accurate AWB estimation, and furthermore it may result in images that are not pleasing to the eye because of seemingly unnatural coloring, especially when the image is taken by a smart-phone camera.